Python
Skill aAAaqwq/AGI-Super-Team/skills/backend-development/python
Python后端开发专家。精通FastAPI、Django、Flask等框架，以及Pydantic、SQLModel、Alembic、Playwright等Python生态最佳实践。From its SKILL.md
npx -y skills add aAAaqwq/AGI-Super-Team --skill pythonAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
1.3 KB, 338 tokens by cl100k_base, as published. Nobody here has run it
Python 后端开发专家
当使用此技能
- 开发现代异步 API (FastAPI)
- 构建企业级全栈应用 (Django)
- 创建轻量级微服务 (Flask)
- 设计数据库 ORM (SQLModel/SQLAlchemy)
- 数据验证 (Pydantic)
- 数据库迁移 (Alembic)
- 浏览器自动化 (Playwright)
框架选择
| 框架 | 适用场景 |
|---|---|
| FastAPI | 现代 API、异步、自动文档 |
| Django | 企业应用、全栈、CMS |
| Flask | 微服务、快速原型 |
最佳实践
- 类型注解: 使用 Python 3.9+ 类型提示
- 异步优先: FastAPI 用 async/await
- Pydantic 验证: 所有输入/输出用 BaseModel
- Alembic 迁移: 数据库变更必须迁移
- 环境配置: 使用 pydantic-settings
- 测试覆盖: pytest + pytest-asyncio
触发词
- "开发 Python API"
- "FastAPI 项目"
- "Django 应用"
- "Python 后端"
- "SQLAlchemy ORM"
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.
Gives 0 of the 12 instructions most data backend skills give in 338 tokens
Counted across 258 of the 277 authors here whose files we hold, read 2026-09-06
- Centralize error handling in one handlerin 38 of 258, across 20 files
- Select only needed columns in queriesin 36 of 258, across 18 files
- Check cache before querying the databasein 36 of 258, across 19 files
- Wrap multi-step writes in transactionsin 36 of 258, across 18 files
- Retry failed requests with exponential backoffin 36 of 258, across 18 files
- Batch fetch related records to avoid N+1 queriesin 34 of 258, across 16 files
- Use resource-based URLs for REST endpointsin 31 of 258, across 13 files
- Separate business logic into a service layerin 29 of 258, across 17 files
- Queue background jobs instead of blocking requestsin 29 of 258, across 14 files
- Abstract data access behind repository interfacesin 25 of 258, across 13 files
- Log structured JSON with request contextin 15 of 258, across 7 files
- Use a shared store for rate limitingin 14 of 258, across 6 files
Said here and by no other author read
- use Python 3.9+ type hints
- write FastAPI handlers with async/await
- validate all inputs and outputs with Pydantic BaseModel
- create an Alembic migration for every database change
- manage configuration with pydantic-settings
- write tests with pytest and pytest-asyncio
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.